Study uncovers how misinformation and fake news can spread via social media platforms like Twitter. Those with high numbers of mutual followers are more likely to spread "dreadful" misinformation. Findings could offer solutions to prevent fake news dissemination.
Linguistic analytic models found users who tweet about loneliness post significantly more frequently about mental health concerns, relationship problems, and insomnia.
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A new deep learning system is 90% accurate in identifying cyberbullies on the popular social media site Twitter.
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Combining artificial intelligence and computer vision technology, researchers were able to determine anxiety and depression risks from peoples' Twitter profile pictures.
Researchers link social media factors to major depressive disorder in Millennials. The study found those with MDD were less likely to post photos of themselves with other people and reported having less social media followers.
Researchers have managed to find a way to measure social 'jet lag', a mismatch between circadian rhythm and the realities of daily schedules, by analyzing patterns of activity on Twitter.
Researchers report Russian trolls and bots are significantly involved in promoting discord and spreading false information about vaccines on Twitter. The study reports these accounts shared anti-vaccination messages 75% more than average Twitter users.
Artificial IntelligenceDeep LearningFeaturedNeuroscienceNeurotechOpen Neuroscience ArticlesPsychology··4 min read
Using AI to examine over 800 million tweets, researchers reveal how our mode of thinking alters during the course of the day. The study reports early morning tweets tend to be correlated with more logical thinking patterns, while middle of the night tweets tend to exhibit more existential concerns.